New Black Bear Data Show Ketchum Sample 26 (the Smeja Kill) is a Bear

PREFACE

I’ve been asked, “Why are we still talking about this?” (the Ketchum paper). At the risk of being presumptuous, I assume this came from those who are convinced that the evidence proves the Ketchum conclusions wrong. In any case,

1. Dr. Melba Ketchum, DVM, continues to appear on sensationalist radio shows arguing for her study and its conclusions before predisposed, sympathetic, biased interviewers and largely uninformed audiences.

2. She dismisses any opposing scientific analysis, not by addressing the technical details, but by claiming her critics have neither the background, education, institutional association, or software tools to make valid judgements about her work, but she doesn’t consistently apply the same criteria to her own coauthors and consultants or herself.

3. Matching DNA sequences at NCBI is a running target, as new data is constantly being added. New data -->> New results -->> Maybe new conclusions (maybe not). Science is always in flux.

4. This has been a learning process for me. As I make new personal (not necessarily new, new) discoveries, I like to share them, which is the purpose of any blog. Others have found my work helpful. 

5. Nobody, particularly from among Ketchum coauthors and consultants, has pointed out any inaccuracies in my work. I have tried unsuccessfully to engage these folks and hope eventually to hear from them. Some won’t even be identified by name. Science has no place for anonymity. If you can’t stand behind your work, why should anybody take it seriously? In this context I have to commend Dr. Ketchum for at least standing up for her work. I take it very seriously.  The blog below took approximately 40 hr to complete and involved dozens of independent searches. 



New Black Bear Data Show Ketchum Sample 26 (the Smeja Kill) is a Bear

by Haskell Hart



ABSTRACT

The nuclear DNA sequence of Sample 26 (the Smeja kill) of the Ketchum study, “Novel North American Hominins: Next Generation Sequencing of Three Whole Genomes and Associated Studies “, was compared to the “Expressed sequence tags” database of the National Center for Biotechnology Information (NCBI) with BLAST(TM) search software.  Fifty-nine hits with %ID ≥ 99% and sequence length ≥200 bp were further compared to the whole genome polar bear sequence in the NCBI Reference genomic sequences database. Results showed a preference for a bear in 58 of 59 matches (one was a dog), with black bear and polar bear best matches about equal in number where both species could be compared. Once again, S26 proves to be a bear, most likely a black bear considering its California origin.


INTRODUCTION

Previous analysis [1] of the Ketchum Sample 26 (S26) - the Smeja kill - nDNA sequence [2] concluded that this sample was a bear, most likely a black bear (Ursus americanus). However, the paucity of black bear sequences in several NCBI databases searched prevented absolute species determination. Instead, giant panda (Ailuropoda melanoleuca) and polar bear (Ursus maritimus) sequences were nearly always the best hits compared to all other species. Later, after its whole genome was available for query in 2014, the polar bear alone had the best hits [3]. Since S26 was from California, it was natural to assume that the only extant bear, the black bear, was the origin. This work will compare the S26 sequence to expressed sequence tags (EST) in the EST database of NCBI, a previously untapped database.

An EST is a nuclear cDNA (complementary DNA) sequence which is produced by cloning the corresponding mRNA sequence obtained from extracts from important organs, e.g. eyes, heart, lung, kidney, liver, or muscle [4]. Each sequence is usually less than 1000 bp (typically a few hundred bp), which makes amplification and sequencing relatively easy compared to whole genome methods. These sequences are often highly conserved (as organs function similarly among different species), so picking the “best” hit from among many “good” hits is critical.  

Fortunately, the EST database contains a large number (38,757) of mostly nonredundant black bear sequences. There are no other bear sequences in this database. By comparison, the popular “nucleotide” database, the only one considered by the Ketchum team, contains only 1663 black bear sequences and 216,511 giant panda and 100,160 polar bear sequences as of this date. Thus, it seemed like an unusual opportunity to search the EST database for black bear (and, of course, other) matches.

 
COMPUTATIONAL METHODS

The S26 nDNA sequence, 2,726,786 bp, was previously downloaded from the online Ketchum paper [1] and, as the query, was not broken down into smaller segments, as is commonly done by others, including the Ketchum consultants. The smaller the segments are, the more likely the match to multiple species, because information is lost.

All searches were against the NCBI “Expressed sequence tags” database with the BLAST(TM) software.  Search parameters were the default ones except that the word size was increased to 64 when the full S26 sequence was queried to conserve CPU and memory. The maximum number of hits was increased to 5,000 so as not to miss any significant matches. All search results were downloaded as Excel .csv files and converted to .xlsx files for further sorting and screening.

 
RESULTS AND DISCUSSION

To start with, we limited the query to black bear matches, which produced a promising list of 1503 black bear matches. The list was sorted by score and %ID. Considering the volume of data and the degree of match, it was decided to consider only those hits with ≥ 200bp and ≥ 99%ID in all future species comparisons. Sorted by score and %ID, we used this list as a check against matches in the general search.

To consider all species matches, a general search was performed (maximum number of database hits 5000) with no species limitations. The list of 22,035 hits (multiple per database hit) was downloaded and sorted by %ID, then length. Culling this list by hand produced a list of all hits satisfying the above criteria. These 59 hits are seen in Table 1. Twenty-nine were black bear, 11 dog, eight human, six pig, one sheep, one deer mouse, one cow, and two that matched many species equally (including some plants).

For those hits which were not a black bear (30), searches over the same S26 sequence ranges were performed against the “Reference genomic sequences” database, limited to polar bear (the closest species to black bear in that database). These hits are listed in bold italics immediately below the corresponding EST hits in Table 1, and are included in Fig. 1.

The black bear hits were also compared to polar bear in the Reference genomic sequences database. These results are also listed, underlined, immediately below each black bear hit in Table 1. These polar bear hits were not included in Fig. 1.

To ensure that all EST hits (bear and nonbear) were the best over their various sequence ranges, the entire hit list was scrutinized in the vicinities of these sequence ranges. The hits generally stood out by %ID and no other competing matches were found.

Overall results can be summarized thusly:

1. 29 of 59 best hits by score and %ID were black bear.

2. Of the 30 non black bear hits, 27 were better matched over the same sequence range by polar bear (bold italics) than by the non bear EST hit. None of these hit sequence ranges had any black bear data in the database.

3. Two matches (15. And 40. In Table 1) were equal: between pig and polar bear and between many species and polar bear, respectively.

4. Only one best match (57. In Table 1) was not a bear but a dog. For confirmation the Reference genomic sequence database was queried limited to dog (third line for no. 58.). This match was also better than the polar bear.

5. Comparing polar bear (underlined) to black bear, 11 of these polar bear hits were better than the corresponding black bear hits, five were equal, and 13 black bear hits were better than polar bear, many of these comparisons were within one mismatch or gap.

A graphic summary of these results over the entire S26 sequence is shown in Fig. 1. The abscissa is the starting position of the hit sequence (“Start” in Table 1) along the 2.7M bp of the S26 sequence. The ordinate is %ID. It is readily seen that generally (with some exceptions), bear hits are concentrated above and non bears below by %ID.


CONCLUSIONS

Before arriving at conclusions, the following points must always be kept in mind:

1. The S26 query sequence represents about 0.1% of an entire mammalian genome, gap not a “whole genome” as proclaimed in the Ketchum title and text.

2. The EST database does not contain complete genomes, only relatively short sequences thought to be important. Only the “Reference genomic sequences” database contains complete genomes, but the number of species there is much less than in the other databases.

3. Not all species are equally represented in the EST database, or in any of the NCBI databases. 

4. Each species may have somewhat different genes represented in the EST database, so that direct comparisons over the same query sequence range may not always be possible.

However, the results above overwhelmingly favor a bear as the origin of S26. Matches to black bear and polar bear where possible were nearly equal. Based on these data alone there was no preference for one bear species over the other. In other words, the genes represented by these sequences are highly conserved, so that a full species determination cannot be made on the basis of only one polar bear specimen in the Reference genomic sequences database and the limited black bear data in the EST database. Intraspecies variation (SNPs) is likely as great as interspecies variation for these two bear species (in the same Ursus genus) over the matching genes in the EST database.

Sample 26 is a bear, based on all EST and polar bear matches with %ID ≥ 99%, and length ≥ 200bp. Only one sequence of 59 matched a dog better, which could be contamination, since the sample was found with the help of a dog. Consistent with these results and considering the California provenance, S26 is very likely a black bear.  Such was the conclusion of three independent laboratories based on their separate sequencing experiments [5].

ACKNOWLEDGEMENT 

Thanks go to Dr. Ketchum for making her S26 sequence available online.
This work received no financial support or other material support.

CONFLICT OF INTEREST

The author declares no competing interests.

REFERENCES

[1] See “Paper 1” link on right.

[2] See “Sasquatch Genome Project” link on right.

[3] See on this blog, November 30, 2014, “Table 1 Updated: The Ketchum Sample 26 nDNA”.

[4] Parkinson J, Blaxter M., Expressed sequence tags: an overview, Methods Mol. Biol., 2009; 533:1-12. doi: 10.1007/978-1-60327-136-3_1.

[5]  See on this blog, November 26, 2014, "Ketchum Sample 26, The Smeja Kill: Independent Lab Reports".


Table 1.  S26 vs. EST Highest Scores, gt 99 %ID, gt 200 bp Length

	ACCESSION	%ID[a]	LEN[b]	MIS[c]	GAPS[d]	Start[e]	End[f]	SCORE[g]	Species
1.	GW310394.1	100	292	0	0	80747	81038	540	black bear
	NW_007927674.1	99.66	292	1	0	80747	81038	534	polar bear
2.	GW298753.1	99.61	259	1	0	162255	162513	473	black bear
	NW_007930700.1	99.61	259	1	0	162255	162513	473	polar bear
3.	GW309384.1	100	682	0	0	184476	185157	1260	black bear
	NW_007929447.1	100	682	0	0	184476	185157	1260	polar bear
4.	GW299178.1	100	310	0	0	213697	214006	573	black bear*
	GW281787.1	99.52	629	3	0	213697	214325	1146	black bear*
	NW_007929448.1	99.84	629	1	0	213697	214325	1157	polar bear
5.	GW308365.1	99.6	248	1	0	247118	247365	455	black bear
	NW_007929448.1	100	248	0	0	247118	247365	459	polar bear
6.	GW291037.1	100	294	0	0	260962	261255	544	black bear
	NW_007929448.1	99.66	294	1	0	260962	261255	538	polar bear
7.	GW292544.1	100	375	0	0	313146	313520	693	black bear
	NW_007907318.1	99.73	375	1	0	313146	313520	688	polar bear
8.	AI573283.1	99.39	494	1	1	343463	343954	894	human
	NW_007907318.1	100	492	0	0	343463	343954	909	polar bear
9.	BE749348.1	99.82	554	1	0	363248	363801	1018	cow
	NW_007907318.1	100	554	0	0	363248	363801	1024	polar bear
10.	GW295806.1	99.42	346	2	0	380277	380622	628	black bear
	NW_007907318.1	100	346	0	0	380277	380622	640	polar bear
11.	GW288445.1	99.26	269	1	1	389816	390083	484	black bear
	NW_007907318.1	100	268	0	0	389816	390083	496	polar bear
12.	GW306627.1	100	253	0	0	495501	495753	468	black bear
	NW_007907078.1	100	253	0	0	495501	495753	468	polar bear
13.	GW298500.1	99.34	304	2	0	542051	542354	551	black bear
	NW_007907078.1	100	304	0	0	542051	542354	562	polar bear
14.	BF974021.1	99.24	264	2	0	673229	673492	477	human
	NW_007907078.1	99.62	265	0	1	673229	673492	483	polar bear
15.	HX217873.1	100	223	0	0	699417	699639	412	pig
	NW_007907078.1	100	223	0	0	699417	699639	412	polar bear
16.	HX217873.1	99.18	367	1	2	700252	700618	660	pig
	NW_007907078.1	100	367	0	0	700252	700618	678	polar bear
17.	GW290970.1	100	264	0	0	749867	750130	488	black bear
	NW_007907078.1	98.86	264	3	0	749867	750130	472	polar bear
18.	CO686642.1	99.7	336	0	1	754448	754783	614	dog
	NW_007907078.1	100	336	0	0	754448	754783	621	polar bear
19.	DN866489.1	99.75	403	1	0	778998	779400	739	dog
	NW_007907078.1	100	403	0	0	778998	779400	745	polar bear
20.	DN431979.1	99.71	341	0	1	779637	779977	623	many
	NW_007907078.1	99.71	341	1	0	779637	779977	625	polar bear
21.	GW292374.1	99.7	329	0	1	780284	780612	601	black bear
	NW_007907078.1	99.09	329	2	1	780284	780612	590	polar bear
22.	DT539446.1	99.68	313	0	1	1041919	1042231	571	dog
	NW_007907185.1	100	313	0	0	1041919	1042231	579	polar bear
23.	AA830903.1	99.15	353	3	0	1043067	1043419	636	human
	NW_007907185.1	100	353	0	0	1043067	1043419	652	polar bear
24.	DN379914.1	99.16	356	3	0	1050478	1050833	641	dog
	NW_007907185.1	99.72	356	1	0	1050478	1050833	652	polar bear
25.	CF411400.1	99.56	459	2	0	1056408	1056866	837	dog
	NW_007907185.1	100	459	0	0	1056408	1056866	848	polar bear
26.	DN442006.1	99.58	236	1	0	1057402	1057637	431	dog
	NW_007907185.1	100	236	0	0	1057402	1057637	436	polar bear
27.	GW279426.1	99.32	443	2	1	1261885	1262326	800	black bear
	NW_007907319.1	94.32	370	20	1	1261885	1262253	566	polar bear
28.	GW291314.1	99.79	473	1	0	1311093	1311565	870	black bear
	NW_007907319.1	97.23	470	0	1	1311093	1311562	784	polar bear
29.	FS641411.1	99.11	224	2	0	1320670	1320893	403	pig
	NW_007907319.1	100	224	0	0	1320670	1320893	414	polar bear
30.	EE822031.1	99.57	234	0	1	1321973	1322206	425	sheep
	NW_007907319.1	100	234	0	0	1321973	1322206	433	polar bear
31.	DT537638.1	99.63	541	1	1	1323769	1324309	987	dog
	NW_007907319.1	100	283	0	0	1323769	1324051	523	polar bear#
	NW_007907319.1	100	86	0	0	1324224	1324309	159	polar bear#
32.	EW079092.2	99.01	303	2	1	1325115	1325416	542	pig
	NW_007907319.1	100	302	0	0	1325115	1325416	558	polar bear
33.	GW287019.1	99.63	269	1	0	1326203	1326471	492	black bear
	NW_007907319.1	99.26	269	2	0	1326203	1326471	486	polar bear
34.	DR423679.1	99	399	4	0	1341810	1342208	715	human
	NW_007907319.1|	99.5	399	2	0	1341810	1342208	726	polar bear
35.	GW314371.1	99.4	332	0	1	1342901	1343230	601	black bear
	NW_007907319.1	99.15	234	0	1	1342999	1343230	420	polar bear
36.	GW306862.1	99.01	404	4	0	1361914	1362317	730	black bear
	NW_007907319.1	100	404	0	0	1361914	1362317	747	polar bear
37.	GW278008.1	99.74	390	1	0	1370591	1370980	717	black bear
	NW_007907319.1	99.74	390	1	0	1370591	1370980	715	polar bear
38.	GW296089.1	100	310	0	0	1387158	1387467	573	black bear
	NW_007907177.1	100	310	0	0	1387158	1387467	573	polar bear
39.	DN273193.1	99.32	294	2	0	1493043	1493336	532	dog
	NW_007907285.1	100	294	0	0	1493043	1493336	544	polar bear
40.	CX057394.1	100	301	0	0	1513922	1514222	556	many
	NW_007907142.1	100	300	0	0	1513923	1514222	555	polar bear
41.	GH523317.1	99.39	488	3	0	1616909	1617396	885	deer mouse
	NW_007907229.1	100	488	0	0	1616909	1617396	902	polar bear
42.	AU131045.1	100	392	0	0	1617005	1617396	725	human
	NW_007907229.1	100	392	0	0	1617005	1617396	725	polar bear
43.	CF411212.1	99	300	3	0	1620530	1620829	538	dog
	NW_007907229.1	99.67	300	0	1	1620530	1620829	547	polar bear
44.	DA189290.1	99.22	255	2	0	1647778	1648032	460	human
	NW_007907229.1	100	255	0	0	1647778	1648032	472	polar bear
45.	DN749512.1	99.36	311	1	1	1663216	1663526	562	dog
	NW_007907230.1	100	311	0	0	1663216	1663526	575	polar bear
46.	EW538766.2	99.36	311	1	1	1663527	1663836	562	pig
	NW_007907230.1	100	310	0	0	1663527	1663836	573	polar bear
47.	DB179765.1	99.22	387	3	0	1805288	1805674	699	human
	NW_007907090.1	100	387	0	0	1805288	1805674	715	polar bear
48.	GW307456.1	99.63	268	1	0	1961310	1961577	490	black bear
	NW_007907111.1	100	268	0	0	1961310	1961577	496	polar bear
49.	GW293348.1	99.66	298	1	0	1971119	1971416	545	black bear
	NW_007907111.1	100	298	0	0	1971119	1971416	551	polar bear
50.	GW309342.1	100	262	0	0	1999882	2000143	484	black bear
	NW_007907111.1	100	262	0	0	1999882	2000143	484	polar bear
51.	GW308592.1	99.78	446	1	0	2000502	2000947	819	black bear
	NW_007907111.1	100	446	0	0	2000502	2000947	824	polar bear
52.	GW287313.1	99.09	331	0	1	2102443	2102770	592	black bear
	NW_007907111.1	98.79	331	1	1	2102443	2102770	586	polar bear
53.	GW298993.1	99.73	371	1	0	2302305	2302675	680	black bear
	|NW_007907111.1	100	371	0	0	2302305	2302675	686	polar bear
54.	DB197414.1	99.09	328	3	0	2430108	2430435	590	human
	NW_007907090.1	100	327	0	0	2430108	2430434	604	polar bear
55.	GW304781.1	99.65	288	1	0	2478714	2479001	527	black bear
	NW_007907090.1	100	288	0	0	2478714	2479001	532	polar bear
56.	GW292148.1	100	247	0	0	2550774	2551020	457	black bear
	No Match								polar bear
57.	DN379546.1	99.31	291	2	0	2560046	2560336	527	dog
	NW_007907090.1	98.61	287	4	0	2560046	2560332	508	polar bear
	NC_006587.3	98.97	291	1	1	2560046	2560336	520	dog+
58.	BW962463.1	99.62	260	0	1	2585217	2585476	473	pig
	NW_007907090.1	100	260	0	0	2585217	2585476	481	polar bear
59.	GW306071.1	100	351	0	0	2654215	2654565	649	black bear
	No Match								polar bear

[a]   Percentage of matching base pairs (bp) over the sequence range Start to End.
[b]  Length of matching sequence, bp.
[c]  Mismatches, bp.
[d]  Gaps-either query or target, number, not bp. 
[e]  Hit starting position on S26 sequence, bp.
[f]  Hit end position on S26 sequence, bp.
[g]  Score, see NCBI BLAST(TM) Handbook.

*     Overlapped.
#     Combined.
+     See Text